This invention relates to a data processing method in a nuclear magnetic resonance (NMR) apparatus. More particularly, it relates to a processing method of data for image reconstruction in the NMR apparatus in the medical field.
Conventionally, two-dimensional fast Fourier transform (2D-FFT) has been used as a method of reconstructing two-dimensional images in the NMR apparatus. According to this method,however, ringing referred to as "truncation artifacts" occurs because a measurement region is limited. A method is known which approaches smoothly measurement data to "0" near the end of a measurement region by the use of filters in order to eliminate the truncation artifacts, but this method involves the problem that resolution drops. To solve this problem, a method which extrapolates appropriate data by linear prediction and reduces the truncation artifacts without lowering resolution has been proposed. However, a computation quantity required for linear prediction is enormous and the reduction of the computation quantity is a key to the practical application of this method.
The following two references are known as the prior art most approximate to the present invention:
"Proceedings of Japanese Magnetic Resonance in Medicine, 16th Meeting", p. 284 (1990).
"Journal of Magnetic Resonance", Vol. 82, pp. 392-399 (1989).
These methods multiply data by a weight and effect linear prediction for the product to reduce the truncation artifacts.